Results 71 to 80 of about 13,903 (231)

Research of output characteristic fitting of eddy-current sensor based on radial-basis function neural network

Gong-kuang zidonghua, 2013
In view of problem that eddy-current sensor cannot reflect measured physical quantity accurately caused by higher nonlinear of output characteristic parameter, the paper proposed a scheme of using RBF neural network to fit output characteristic parameter
YOU Wen-jian, LIANG Bing, LI Yin-jun
doaj  

High-Dimensional Aerodynamic Modeling Prediction Based on Modified RBF Neural Network with Data Assimilation

气体物理
In this paper, the radial basis function (RBF) neural network was modified by data assimilation method to improve the modeling accuracy of high-dimensional aerodynamics. A correction factor γ was introduced into the kernel function of the traditional RBF
Ying ZHANG, Xin ZHANG, Weiguo ZHANG, Zichen DENG   +3 more
doaj   +1 more source

RBF-MLMR: A Multi-Label Metamorphic Relation Prediction Approach Using RBF Neural Network

IEEE Access, 2017
Metamorphic testing has been successfully used in many different fields to solve the test oracle problem. However, how to find a set of appropriate metamorphic relations for metamorphic testing remains a complicated and tedious task.
Pengcheng Zhang, Xuewu Zhou, Patrizio Pelliccione, Hareton Leung   +3 more
doaj   +1 more source

From Planar to 3D Nanophotonic Lenses: Advancing Design, Fabrication, and Applications

Laser &Photonics Reviews, EarlyView.
Three‐dimensional nanophotonic lenses are enabled by an integrated workflow that links design parameterization, full‐wave electromagnetic simulation, computational optimization, and freeform fabrication. This Review summarizes how these tools expand optical design freedom beyond a single patterned plane by enriching the local meta‐atom response and ...
Wei Zhu, Lyudmila V. Goncharova, Eric Johlin   +2 more
wiley   +1 more source

A New Localization Algorithm Based on Taylor Series Expansion for NLOS Environment

Cybernetics and Information Technologies, 2016
In Non-Line-Of-Sight (NLOS) environment, location accuracy of Taylorseries expansion location algorithm degrades greatly. A new Taylor-series expansion location algorithm based on self-adaptive Radial-Basis-Function (RBF) neural network is proposed in ...
Ren Jin, Chen Jingxing, Bai Wenle
doaj   +1 more source

Multi‐Objective Bayesian Co‐Optimization of Parameterized Moving Horizon Estimation and Model Predictive Control

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT This paper proposes a Machine Learning (ML)‐enabled estimator‐controller design framework, in which a parameterized Model Predictive Controller (MPC) and a parameterized Moving Horizon Estimator (MHE) are jointly refined using Bayesian Optimization (BO).
Hossein Nejatbakhsh Esfahani, Javad Mohammadpour Velni   +1 more
wiley   +1 more source

Phase transmittance RBF neural networks

Electronics Letters, 2007
Presented is a new complex valued radial basis function (RBF) neural network with phase transmittance between the input nodes and output, which makes it suitable for channel equalisation on quadrature digital modulation systems.
D.V. Loss, M.C.F. DeCastro, P.R.G. Franco, F.C.C. DeCastro   +3 more
openaire   +1 more source

Key Technical Fields and Future Outlooks of Space Manipulators: A Survey

SmartBot, EarlyView.
This paper systematically reviews the technological development of space manipulators, emphasizing the unique challenges posed by space environments. It examines four areas: structural design, modeling, planning, and control, while introducing typical ground test platforms.
Gang Chen, Zeyuan Huang, Ying Yan, Xiaokang An, Zhikai Zhao, Jirong Lin, Xiangrong Zhao, Xianyuan Gao, Junyi Zong, Xuewen Jia, Zhipeng Yao, Jianliang Liao, Ning Ji   +12 more
wiley   +1 more source

Fiber Bragg Grating Force Sensors for Minimally Invasive Surgery: State of the Art, Challenges, and Opportunities

SmartBot, EarlyView.
This article reviews the application of fiber Bragg grating (FBG) technology for precise force sensing in minimally invasive surgery. It outlines the fundamental working principles and algorithms used to interpret sensor data. The text surveys clinical applications across various medical fields, such as ophthalmology and vascular intervention (Table of
Shiyuan Dong, Tianqi Huang, Lingyu Chen, Shucong Yin, Qing Chang, Dingpei Han, Yangxi Li, Boyu Zhang, Hongen Liao, Fang Chen   +9 more
wiley   +1 more source

Network Latency Estimation for Telesurgery Using Deep Reinforcement Learning

SmartBot, EarlyView.
Overview of the proposed two‐stage deep reinforcement learning framework for network latency prediction in telesurgery. The pipeline includes data collection from simulated catheter navigation sessions (Philippines–Botswana), feature engineering, DQN‐based direction prediction (85.8% accuracy), direction‐to‐value transformation, and value forecasting ...
Bakang Kgopolo, Rodrigo S. Jamisola Jr., Molaletsa Namoshe   +2 more
wiley   +1 more source